Diabetes Mellitus Impacts on Lung Cancer Prognosis
Summary
Lung cancer remains one of the leading causes of cancer mortality worldwide, and diabetes mellitus is a common comorbidity that can influence both the biology of the tumour and the patient’s ability to tolerate and respond to therapy. Chronic hyperglycaemia and insulin resistance may promote tumour growth through enhanced availability of metabolic substrates and activation of the insulin–IGF axis, leading to increased cell proliferation, angiogenesis and resistance to apoptosis. In addition, diabetes is often accompanied by systemic inflammation, endothelial dysfunction and altered immune surveillance, all of which may contribute to more aggressive disease behaviour. Clinically, patients with pre-existing diabetes frequently present with higher rates of postoperative complications, diminished tolerance to chemoradiotherapy and shorter progression-free and overall survival. Conversely, rigorous glycaemic control has been associated with improved treatment efficacy and prolonged survival. A clear understanding of the bidirectional interactions between glycaemic status and lung cancer outcomes is essential for optimising multidisciplinary care and guiding personalised treatment strategies.
Research from Nature Portfolio
No recent Nature Portfolio content available.
Diabetes Mellitus Impacts on Lung Cancer Prognosis publication trend
The graph below shows the total number of articles in diabetes mellitus impacts on lung cancer prognosis across all publications each year (not limited to Nature Index journals).
Technical terms
Diabetes Mellitus: A metabolic disorder characterised by chronic hyperglycaemia due to insulin deficiency or resistance.
Non-Small Cell Lung Cancer (NSCLC): The most common category of lung cancer, including adenocarcinoma, squamous cell carcinoma and large cell carcinoma.
Glycated Haemoglobin (HbA1c): A measure of average blood glucose concentrations over the preceding two to three months.
Progression-Free Survival (PFS): The length of time during and after treatment in which a patient’s disease does not worsen.
Overall Survival (OS): The duration from diagnosis or start of treatment until death from any cause.
Propensity Score Matching (PSM): A statistical method that pairs patients with similar baseline characteristics across comparison groups to reduce confounding in observational studies.
References
- Hyperglycemia and Lung Cancer—A Possible Relationship. Diagnostics (2025).
- Prognostic significance of diabetes mellitus in locally advanced non-small cell lung cancer. BMC Cancer (2015).
- Impact of diabetes mellitus on postoperative outcomes in individuals with non-small-cell lung cancer: A retrospective cohort study. PLOS ONE (2020).
- Poor glycemic control might compromise the efficacy of chemotherapy in non‐small cell lung cancer patients with diabetes mellitus. Cancer Medicine (2019).
- The Survival Benefit for Optimal Glycemic Control in Advanced Non-Small Cell Lung Cancer Patients With Preexisting Diabetes Mellitus. Frontiers in Oncology (2021).
- Long‐term survival analysis of patients with stage IIIB‐IV non‐small cell lung cancer complicated by type 2 diabetes mellitus: A retrospective propensity score matching analysis. Thoracic Cancer (2022).
Turn complex research questions into confident strategic decisions
When you're under pressure to set direction, justify investment, or understand your competitive position, you need more than raw data — you need trusted insights you can act on.
Benchmark your performance against global peers using robust, methodologically sound analysis.
Combine quantitative metrics with qualitative expert insight to uncover strengths, gaps and emerging opportunities.
Gain tailored, decision-ready recommendations aligned to your strategic priorities.
Talk to us to learn more about our data dashboards and bespoke strategy reports.
Grow research skills, confidence and careers with training built for every stage of the research lifecycle.
Developed with Nature Portfolio journal Editors and internationally renowned experts. Discover three ways to learn:
Self-paced, online courses in convenient bite-sized units, covering key skills across scientific writing, publishing, grant writing, data analysis, and more.
Expert trainer-led workshops with hands-on exercises and real-time feedback across core research skills, delivered via interactive group sessions.
Editor-led workshops combining core principles in writing and publishing, personalised 1:1 feedback from Nature Portfolio Editors and hands-on exercises.
Explore course catalogues and workshop agendas, enquire about the options or request institutional pricing.